Tremor Control Devices for Essential Tremor: A Systematic Literature Review

Background: There is a growing interest in nonpharmacological approaches for essential tremor (ET), including tremor cancelation devices. However, the true efficacy of such devices in ET remains unclear. Methods: A systematic literature review was conducted using standardized criteria regarding efficacy and comfortability. Devices focused on design or experimental testing in which tremor was simulated in a robot were excluded. Results: Out of 324 articles initially identified, 12 articles were included. Orthoses using biomechanical loading and neuromodulation with electrical stimulation, and external tremor cancelation devices, were the main interventions used to suppress tremor. All devices were designed to control tremor of the upper limbs at different anatomical locations. Overall, an average tremor attenuation of 50–98% was reported (level of evidence III). Interference with voluntary movements and portability was described as the main drawback. Discussion: In conclusion, this review highlights the growing interest in emerging tremor control devices and the importance of assessing comfort without affecting voluntary movements. However, the level of evidence regarding the efficacy of these tremor control devices remains low. An integrated multidisciplinary combination approach of engineering, robotics, physiology, physiotherapy, and clinical assessment is needed to improve the quality of non-pharmacological interventions for ET

A virtual hand assessment system for efficient outcome measures of hand rehabilitation

Previously held under moratorium from 1st December 2016 until 1st December 2021.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control

Neurological Tremor: Sensors, Signal Processing and Emerging Applications

Neurological tremor is the most common movement disorder, affecting more than 4% of elderly people. Tremor is a non linear and non stationary phenomenon, which is increasingly recognized. The issue of selection of sensors is central in the characterization of tremor. This paper reviews the state-of-the-art instrumentation and methods of signal processing for tremor occurring in humans. We describe the advantages and disadvantages of the most commonly used sensors, as well as the emerging wearable sensors being developed to assess tremor instantaneously. We discuss the current limitations and the future applications such as the integration of tremor sensors in BCIs (brain-computer interfaces) and the need for sensor fusion approaches for wearable solutions

A Wearable Mechatronic Device for Hand Tremor Monitoring and Suppression: Development and Evaluation

Tremor, one of the most disabling symptoms of Parkinson\u27s disease (PD), significantly affects the quality of life of the individuals who suffer from it. These people live with difficulties with fine motor tasks, such as eating and writing, and suffer from social embarrassment. Traditional medicines are often ineffective, and surgery is highly invasive and risky. The emergence of wearable technology facilitates an externally worn mechatronic tremor suppression device as a potential alternative approach for tremor management. However, no device has been developed for the suppression of finger tremor that has been validated on a human. It has been reported in the literature that tremor can be selectively suppressed by mechanical loading. Therefore, the objectives of this thesis were to develop a wearable tremor suppression device that can suppress tremor at the wrist and the fingers, and to evaluate it on individuals with PD in a pre-clinical trial. To address these objectives, several experiments were performed to quantify hand tremor; an enhanced high-order tremor estimator was developed and evaluated for tremor estimation; and a wearable tremor suppression glove (WTSG) was developed to suppress tremor in the index finger metacarpophalangeal (MCP) joint, the thumb MCP joint, and the wrist. A total of 18 individuals with PD were recruited for characterizing tremor. The frequencies and magnitudes of the linear acceleration, angular velocity, and angular displacement of tremor in the index finger MCP joint, the thumb MCP joint, and the wrist were quantified. The results showed that parkinsonian tremor consists of multiple harmonics, and that the second and third harmonics cannot be ignored. With the knowledge of the tremor characteristics, an enhanced high-order tremor estimator was developed to acquire better tremor estimation accuracy than its lower-order counterpart. In addition, the evaluation of the WTSG was conducted on both a physical tremor simulator and on one individual with PD. The results of the simulation study proved the feasibility of using the WTSG to suppress tremor; and the results of the evaluation on a human subject showed that the WTSG can suppress tremor motion while allowing the user to perform voluntary motions. The WTSG developed as a result of this work has demonstrated the feasibility of managing hand tremor with a mechatronic device, and its validation on a human subject has provided useful insights from the user\u27s perspectives, which facilitate the transition of the WTSG from the lab to the clinic, and eventually to commercial use. Lastly, an evaluation studying the impact of suppressed tremor on unrestricted joints was conducted on 14 individuals with PD. The results showed a significant increase in tremor magnitude in the unrestricted distal joints when the motions of the proximal joints were restricted. The average increase of the tremor magnitude of the index finger MCP joint, the thumb MCP joint, the wrist and the elbow are 54%, 96%, 124%, and 98% for resting tremor, and 50%, 102%, 49%, and 107% for postural tremor, respectively. Such a result provided additional clinical justification for the significance of the development of a wearable mechatronic device for hand tremor management. Although the focus of this thesis is on hand tremor management, the development and evaluation of a full upper-limb tremor suppression device is required as a future step, in order to advance the use of wearable mechatronic devices as one of the valid tremor treatment approaches

Towards the Development of a Wearable Tremor Suppression Glove

Patients diagnosed with Parkinson’s disease (PD) often associate with tremor. Among other symptoms of PD, tremor is the most aggressive symptom and it is difficult to control with traditional treatments. This thesis presents the assessment of Parkinsonian hand tremor in both the time domain and the frequency domain, the performance of a tremor estimator using different tremor models, and the development of a novel mechatronic transmission system for a wearable tremor suppression device. This transmission system functions as a mechatronic splitter that allows a single power source to support multiple independent applications. Unique features of this transmission system include low power consumption and adjustability in size and weight. Tremor assessment results showed that the hand tremor signal often presents a multi-harmonics pattern. The use of a multi-harmonics tremor model produced a better estimation result than using a monoharmonic tremor model

Robotics in health care: Perspectives of robot-aided interventions in clinical practice for rehabilitation of upper limbs

This article belongs to the Special Issue Rehabilitation Robotics: Recent Advancements and New Perspectives about Training and Assessment of Sensorimotor Functions.Robot-aided systems to support the physical rehabilitation of individuals with neurological impairment is one of the fields that has been widely developed in the last few decades. However, the adoption of these systems in clinical practice remains limited. In order to better understanding the causes of this limitation, a systematic review of robot-based systems focused on upper extremity rehabilitation is presented in this paper. A systematic search and review of related articles in the literature were conducted. The chosen works were analyzed according to the type of device, the data analysis capability, the therapy method, the human–robot interaction, the safety strategies, and the focus of treatment. As a conclusion, self-adaptation for personalizing the treatments, safeguarding and enhancing of patient–robot interaction towards training essential factors of movement generation into the same paradigm, or the use of lifelike environments in fully-immersive virtual reality for increasing the assimilation of motor gains could be relevant factors to develop more accepted robot-aided systems in clinical practice.This work was supported in part by the Spanish Ministry of Economy and Competitiveness via the ROBOESPASproject (DPI2017-87562-C2-1-R) and in part by the RoboCity2030-DIH-CMMadrid Robotics Digital Innovation Hub ("Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, Fase IV"; S2018/NMT-4331), which is funded by the Programas de Actividades I+DComunidad de Madrid and cofunded by the Structural Funds of the EU

Is it possible to assess the effects of dynamic arm supports on upper extremity range of motion during activities of daily living in the domestic setting using a portable motion capturing device? - A pilot study

BACKGROUND: Understanding how dynamic arm supports affect the ability to perform activities of daily living (ADL) in daily life situations is essential for improved prescription. OBJECTIVE: To determine whether the newly developed MMAAS is a useful tool to assess the RoM at home. Secondly, to investigate differences in RoM and ADL performance with and without dynamic arm support. METHODS: Five dynamic arm support users performed nine activities with and without dynamic arm support at home. A reference group of five participants was included. Shoulder and elbow RoM were assessed for the three most difficult tasks. RESULTS: The measurement of the elbow joint RoM appeared unreliable. In most participants shoulder RoM increased with dynamic arm support, but the magnitude of change differed. Variation was also found regarding whether people could perform ADL with and without support. CONCLUSIONS: In its current state the MMAAS is not regarded a useful tool for assessing the RoM in the domestic setting. The ability to perform ADL and RoM seem influenced by the environment, users' needs and abilities. Future studies investigating effects and benefits of dynamic arm supports should be conducted in a broader daily life context

Analytical modelling of a dynamic vibration absorber for Parkinson disease

Parkinson is the most common neurodegenerative disease. It is characterized by the presence of involuntary tremor of human arms. Current treatments as pharmacological and surgery can be invasive for patients due to secondary effects and also high costs are required. In this sense, non-invasives devices have been proposed in order to reduce the tremor amplitude without secondary effects. These devices require a model in order to analyze the dynamic behavior and calculate the optimum parameters. In this article, it is developed an analytical three-dimensional model of a dynamic vibration absorber placed on a human arm. Results show dynamic vibration absorber is effective to reduce the tremor during voluntary motion. However, it is only effective while tremor frequencies are within a narrow range around the tuned frequency used for calculation of absorber parameters